Juha Koivisto is a Research Fellow at the Department of Applied Physics, Aalto University, specializing in complex systems and materials. His work focuses on the mechanical behavior of materials such as foams, hydrogels, and alloys, with applications in sustainable construction and advanced manufacturing. Education: Doctoral degree in Engineering and Technology, Aalto University (awarded October 16, 2013) Master's degree in Engineering and Technology, Helsinki University of Technology (awarded September 18, 2007) Research Interests: His research spans rheology, creep, crack propagation, strain rate effects, and digital image correlation. He investigates the mechanical properties of bio-based materials, including foams and hydrogels, often integrating machine learning and computational modeling. His work contributes to sustainable development, particularly in green building materials and plastic alternatives. Recent Research Trends: His recent publications (2023–2025) reveal a strong focus on sustainable materials, including bio-based foams and coatings, rheological modeling with machine learning (e.g., Gaussian Process Regression), and open-source software development (pyRheo). He also explores smart, adaptive materials for 4D printing applications, demonstrating a blend of experimental physics and computational innovation. Scientific Awards: Advising and Grants: Juha Koivisto has supervised at least two theses, indicating his role in mentoring early-career researchers. He is the Principal Investigator of the EU-funded ARCHIBIOFOAM project (2024–2027), which focuses on digital design and robotic fabrication of biofoams for adaptive architecture. This project highlights his leadership in interdisciplinary, grant-funded research aimed at sustainable construction. Labs and Teams: He is part of the Complex Systems and Materials research group at Aalto University, collaborating with Prof. Mikko Alava and others. His team works on experimental and computational aspects of material failure, rheology, and smart material design, frequently using advanced techniques like digital image correlation and acoustic emission monitoring.